MAVIS ( IN DEVELOPMENT )

Multi-model Animal Vitality Intelligence System

1. Overview

MAVIS is a professional-grade, AI-driven IoT health monitoring system designed to track and analyze animal vitality metrics in real-time. By leveraging a layered backend architecture, it provides robust data integrity and instant physiological insights to ensure animal well-being.

2. Tech Stack

• Backend: Node.js (ES6 Modules), Express.js
• Real-time: Socket.IO for live physiological alerts
• Validation: Joi (Schema-based data integrity)
• Database: MongoDB via Mongoose ODM
• DevOps: Docker & Docker Compose (Containerized Environment)
• Monitoring: Nodemon for hot-reloading during development

3. Architecture & Design Patterns

This project implements a Clean Layered Architecture to ensure scalability and maintainability.

• Controller-Service-Repository Pattern: Decouples HTTP handling, business logic, and data access.
• Dependency Injection: Promotes loose coupling by passing dependencies (like repositories into services) via constructors.
• Singleton Pattern: Ensures resource efficiency by utilizing a single instance of the repository across the app.
• Middleware Validation: A dedicated gatekeeper layer using Joi schemas to validate sensor data before it reaches the core logic.

4. Project Structure

The project is organized into a root orchestrator and modular backend components:

MAVIS/
├── backend/                # Express API & Core Logic
│   ├── config/             # Database & App configurations
│   ├── controllers/        # Request handling & Response formatting
│   ├── middlewares/        # Joi validation & CORS logic
│   ├── models/             # Mongoose Data Schemas
│   ├── repositories/       # Data Access Layer (Singleton)
│   ├── routes/             # API Endpoint definitions
│   ├── services/           # Business Logic & Socket.IO Alerts
│   ├── schemas/            # Joi Validation Rules
│   ├── Dockerfile          # Backend container definition
│   └── server.js           # Entry point
├── frontend/               # (Planned) React/Vite UI
├── .dockerignore           # Excludes node_modules from Docker builds
├── docker-compose.yml      # Root Orchestrator for Backend & MongoDB
└── README.md               # Project Documentation

5. Intelligent Features

• Fever Detection: Instant alerts triggered if animal temperature exceeds 45°C.
• Battery Monitoring: Automated warnings when wearable device battery drops below 20%.
• Historical Analysis: Efficient range-based querying for health trend visualization.
• Real-time Updates: Live data broadcasting via Socket.IO "sensorUpdate" events.

6. Development Setup

Prerequisites

• Docker & Docker Desktop installed.
• Node.js (Optional, as the environment is containerized).

Steps to Run

1. Clone the repository:

git clone <your-repo-link>
cd MAVIS

2. Environment Configuration: Create a .env file inside the /backend folder:

PORT=5000
MONGO_URI=mongodb://db:27017/mavis

3. Launch the System: Run the following command from the Project Root:

docker compose up --build

4. Accessing the App:

• Backend API: http://localhost:5000
• MongoDB: mongodb://localhost:27017 (Connect via MongoDB Compass)

7. Docker Orchestration Details

• Hot Reloading: The /backend folder is volume-mounted so changes in VS Code trigger Nodemon inside the container.
• Data Persistence: Uses a named Docker volume (mongo-data) to ensure sensor records persist between restarts.
• Optimized Builds: A root-level .dockerignore prevents local node_modules from causing architecture conflicts inside the Linux container.